Spatial analysis improves species distribution modelling during range expansion

Species distribution models (SDMs) assume equilibrium between species' distribution and the environment. However, this assumption can be violated under restricted dispersal and spatially autocorrelated environmental conditions. Here we used a model to simulate species' ranges expansion under two non-equilibrium scenarios, evaluating the performance of SDM coupled with spatial eigenvector mapping. The highest fit is for the models that include space, although the relative importance of spatial variables during the range expansion differs in the two scenarios. Incorporating space to the models was important only under colonization-lag non-equilibrium, under the expected scenario. Thus, mechanisms that generate range cohesion and determine species' distribution under climate changes can be captured by spatial modelling, with advantages compared with other techniques and in line with recent claims that SDMs have to account for more complex dynamic scenarios.     

Models for forest ecosystem management: a European perspective

BACKGROUND: Forest management in Europe is committed to sustainability. In the face of climate change and accompanying risks, however, planning in order to achieve this aim becomes increasingly challenging, underlining the need for new and innovative methods. Models potentially integrate a wide range of system knowledge and present scenarios of variables important for any management decision. In the past, however, model development has mainly focused on specific purposes whereas today we are increasingly aware of the need for the whole range of information that can be provided by models. It is therefore assumed helpful to review the various approaches that are available for specific tasks and to discuss how they can be used for future management strategies. SCOPE: Here we develop a concept for the role of models in forest ecosystem management based on historical analyses. Five paradigms of forest management are identified: (1) multiple uses, (2) dominant use, (3) environmentally sensitive multiple uses, (4) full ecosystem approach and (5) eco-regional perspective. An overview of model approaches is given that is dedicated to this purpose and to developments of different kinds of approaches. It is discussed how these models can contribute to goal setting, decision support and development of guidelines for forestry operations. Furthermore, it is shown how scenario analysis, including stand and landscape visualization, can be used to depict alternatives, make long-term consequences of different options transparent, and ease participation of different stakeholder groups and education. CONCLUSIONS: In our opinion, the current challenge of forest ecosystem management in Europe is to integrate system knowledge from different temporal and spatial scales and from various disciplines. For this purpose, using a set of models with different focus that can be selected from a kind of toolbox according to particular needs is more promising than developing one overarching model, covering ecological, production and landscape issues equally well.     

生物多样性与生态系统服务情景模拟研究进展

生物多样性和生态系统服务情景模拟是指对未来生物多样性和生态系统服务变化轨迹的定量估计,二者相互关联并为长期、稳定的保护和恢复生态系统提供了重要科学依据。梳理生物多样性以及生态系统服务预测情景的核心观点,讨论基于生物多样性和生态系统服务情景模拟的保护决策支持途径,以期服务于我国生物多样性与生态系统服务预测研究的发展和深化。研究凝练结果如下:物种分布模型需要进行更规范的评价以明晰其对具体对象的适用性,生态系统预测模型亟待在关系结构的基础上嵌入更多的生态系统过程和社会经济过程,生态系统服务评估模型有必要强化对生物多样性、生态系统服务、人类福祉级联特征的刻画;全球气候变化驱动了未来区域生物多样性的大幅改变;土地利用则是陆地生态系统服务预测中的核心驱动变量。生态区划与区域尺度情景模拟、景观尺度下的生态安全格局构建、基于社会生态网络的社区适应三点重要展望方向将对基于情景模拟的我国生态系统保护决策提供重要的理论和实践支持。     

岷江上游4个栽培树种细根功能性状垂直分布的差异性

细根(直径≤2 mm)功能性状及垂直分布格局是反映植物对土壤资源吸收策略和影响森林地下生态过程的关键。本研究以岷江上游4个人工林树种连香树(Cercidiphyllum japonicum)、白桦(Betula platyphylla)、华山松(Pinus armandii)和油松(P. tabuliformis)为对象,调查不同海拔树木细根功能性状及其在不同土层间的垂直分布格局,并分析细根功能性状分布与构型之间的相关关系。结果表明:阔叶树种比针叶树种有更大的根长密度、生物量、比根长和比表面积,而直径反之; 4个树种细根集中在0～20 cm土层,根长密度和生物量在较高海拔地段均显著大于较低海拔,且均随土壤深度增加而减少,但比根长、比表面积和直径无显著的海拔差异,随土层加深也无明显的垂直变化规律;针阔树种间的细根构型差异显著,但不受海拔差异的影响,阔叶树的细根分支强度与一级根数量显著大于针叶树种;一级根数和根尖密度与比根长以及分根比与根长密度和生物量均呈显著正相关,而分叉与几个细根功能参数均呈负相关;随着土层深度增加,细根总生长量明显减少,但细根资源利用效率和策略不变; 5个细根功能性状...     

Analysis of microsatellite variation in Pinus radiata reveals effects of genetic drift but no recent bottlenecks

Most conifer species occur in large continuous populations, but radiata pine, Pinus radiata, occurs only in five disjunctive natural populations in California and Mexico. The Mexican island populations were presumably colonized from the mainland millions of years ago. According to Axelrod (1981), the mainland populations are relicts of an earlier much wider distribution, reduced some 8,000 years ago, whereas according to Millar (1997, 2000), the patchy metapopulation-like structure is typical of the long-term population demography of the species. We used 19 highly polymorphic microsatellite loci to describe population structure and to search for signs of the dynamics of population demography over space and time. Frequencies of null alleles at microsatellite loci were estimated using an approach based on the probability of identity by descent. Microsatellite genetic diversities were high in all populations [expected heterozygosity (H(e)) = 0.68-0.77], but the island populations had significantly lower estimates. Variation between loci in genetic differentiation (F(ST)) was high, but no locus deviated statistically significantly from the rest at an experiment wide level of 0.05. Thus, all loci were included in subsequent analysis. The average differentiation was measured as F(ST) = 0.14 (SD 0.012), comparable with earlier allozyme results. The island populations were more diverged from the other populations and from an inferred common ancestral gene pool than the mainland ones. All populations showed a deficiency of expected heterozygosity given the number of alleles, the mainland populations more so than the island ones. The results thus do not support a recent important contraction in the mainland range of radiata pine.     

Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah

In this study, we test for the key bioclimatic variables that significantly explain the current distribution of plant species richness in a southern African ecosystem as a preamble to predicting plant species richness under a changed climate. We used 54,000 records of georeferenced plant species data to calculate species richness and spatially interpolated climate data to derive nineteen bioclimatic variables. Next, we determined the key bioclimatic variables explaining variation in species richness across Zimbabwe using regression analysis. Our results show that two bioclimatic variables, that is, precipitation of the warmest quarter (R² = 0.92, P < 0.001) and temperature of the warmest month (R² = 0.67, P < 0.001) significantly explain variation in plant species richness. In addition, results of bioclimatic modelling using future climate change projections show a reduction in the current bio‐climatically suitable area that supports high plant species richness. However, in high‐altitude areas, plant richness is less sensitive to climate change while low‐altitude areas show high sensitivity. Our results have important implications to biodiversity conservation in areas sensitive to climate change; for example, high‐altitude areas are likely to continue being biodiversity hotspots, as such future conservation efforts should be concentrated in these areas.     

Insect photoperiodism: effects of temperature on the induction of insect diapause and diverse roles for the circadian system in the photoperiodic response

This review considers the effects of temperature on insect diapause induction and the photoperiodic response, and includes constant temperature, temperature cycles, pulses and steps in daily light–dark cycles, constant darkness and in constant light, all with reference to various circadian‐based “clock” models. Although it is a comparative survey, it concentrates on two species, the flesh fly Sarcophaga argyrostoma and its pupal parasite Nasonia vitripennis, which possess radically different photoperiodic mechanisms, although both are based upon the circadian system. Particular attention is given to the effects of daily thermoperiod in darkness and to low and high temperature pulses in conjunction with a daily light–dark cycle, treatments that suggest that S. argyrostoma “measures” night length with a “clock” of the external coincidence type. However, N. vitripennis responds to seasonal changes in photoperiod with an internal coincidence device involving both “dawn” and “dusk” oscillators. Other species may show properties of both external and internal coincidence. Although the precepts of external coincidence have been well formulated and supported experimentally, those for internal coincidence remain obscure.     

The effect of resorption cavities on bone stiffness is site dependent

Resorption cavities formed during the bone remodelling cycle change the structure and thus the mechanical properties of trabecular bone. We tested the hypotheses that bone stiffness loss due to resorption cavities depends on anatomical location, and that for identical eroded bone volumes, cavities would cause more stiffness loss than homogeneous erosion. For this purpose, we used beam–shell finite element models. This new approach was validated against voxel-based FE models. We found an excellent agreement for the elastic stiffness behaviour of individual trabeculae in axial compression (R² = 1.00) and in bending (R²>0.98), as well as for entire trabecular bone samples to which resorption cavities were digitally added (R² = 0.96, RMSE = 5.2%). After validation, this new method was used to model discrete cavities, with dimensions taken from a statistical distribution, on a dataset of 120 trabecular bone samples from three anatomical sites (4th lumbar vertebra, femoral head, iliac crest). Resorption cavities led to significant reductions in bone stiffness. The largest stiffness loss was found for samples from the 4th lumbar vertebra, the lowest for femoral head samples. For all anatomical sites, resorption cavities caused significantly more stiffness loss than homogeneous erosion did. This novel technique can be used further to evaluate the impact of resorption cavities, which are known to change in several metabolic bone diseases and due to treatment, on bone competence.     

Adjusting for Nonignorable Missingness When Estimating Generalized Additive Models

Generalized additive models (GAMs) have been widely used for flexible modeling of various types of outcomes. When the outcome in a GAM is subject to missing, practical analyses often assume that missingness is missing at random (MAR). This assumption can be of suspicion when the missingness is not by design. Evaluating the potential effects of alternative nonignorable missing data mechanism on the MAR inference from a GAM can be important but often challenging due to the complicatedness of alternative nonignorable models. We apply the index approach to local sensitivity (Troxel, Ma, and Heitjan 2004 (2004). Statistica Sinica 14 , 1221–1237) to evaluate the potential changes of the GAM estimates in the neighborhood of the MAR model. The approach avoids fitting any complicated nonignorable GAM. Only MAR estimates are required to calculate the resulting sensitivity index and adjust the GAM estimates to account for nonignorable missingness. Thus the proposed approach is considerably simpler to conduct, as compared with the alternative methods. The simulation study shows that the index provides valid assessment of the local sensitivity of the GAM estimates to nonignorable missingness. We then illustrate the method using a rheumatoid arthritis clinical trial data set.